Note: The job is a remote job and is open to candidates in USA. BC Ferries operates an essential transportation network in British Columbia and is modernizing its technology landscape through an enterprise data platform. The Senior Data Engineer will design and deliver scalable data pipelines and enterprise data products that support reporting, analytics, artificial intelligence, operational efficiency, and strategic decision-making.
Responsibilities
- Designing, building, and maintaining complex, production-grade data pipelines and transformations across Bronze, Silver, and Gold layers, ensuring reliable integration, monitoring, performance optimization, and reusable enterprise data products
- Designing and maintaining robust Data Lakehouse data models, dimensional models, and transformation patterns that prepare standardized, analytics-ready data for reporting, enterprise data products, and semantic consumption
- Building and delivering trusted, reusable Gold-layer data products aligned with enterprise data standards, governance requirements, reporting needs, and approved business use cases
- Implementing and maintaining data governance, data quality controls, validation rules, reconciliation processes, and conformance checks to ensure enterprise data is accurate, reliable, secure, and auditable
- Optimizing data models, pipelines, transformations, and processing patterns to maximize performance, scalability, operational reliability, security, and cloud cost efficiency (FinOps)
- Designing and implementing secure data models and transformation processes that embed enterprise access controls, data classifications, governance policies, lineage, and auditability requirements
- Collaborating with Platform Data Engineers, Analytics Engineers, Data Governance partners, and business stakeholders to develop scalable, secure, and high-performing data solutions that meet business and technical requirements
- Leading the troubleshooting, root cause analysis, and resolution of complex pipeline failures, transformation issues, data quality concerns, and production support incidents
- Maintaining technical metadata, data lineage, documentation, source-to-target mappings, coding standards, and reusable engineering practices to ensure enterprise data assets remain understandable, discoverable, and maintainable
- Applying software engineering best practices, including version control, code reviews, automated testing, CI/CD, release management, platform modernization, and technical debt reduction to continuously improve the enterprise data platform
Skills
- A bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Data Analytics, Business Technology, or a related discipline (a master's degree is an asset)
- A minimum of 5-8 years of hands-on experience designing, developing, and supporting enterprise data platforms and modern data solutions
- Strong expertise developing scalable data pipelines using SQL, Python, and PySpark
- Experience with cloud-based data platforms, modern data architectures, and enterprise data engineering practices
- Strong knowledge of dimensional data modelling, data warehousing, and data transformation techniques
- Experience implementing data governance, security, lineage, and data quality controls
- Familiarity with software engineering practices including Git, CI/CD, automated testing, and code reviews
- Excellent analytical, problem-solving, and communication skills, with the ability to work effectively across technical and business teams
Benefits
- Opportunities for growth
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